Design, develop, and implement robust data architecture solutions utilizing modern day data platforms like Snowflake and Databricks.
Ensure scalable, reliable, and secure data environments that meet business requirements and support advanced analytics.
Lead the migration of data from traditional RDBMS systems to Snowflake and Databricks environments.
Architect and design scalable data pipelines and infrastructure to support the organization's data needs.
Develop and manage ETL processes using Snowflake and Databricks to ensure efficient data extraction, transformation, and loading.
Optimize ETL workflows to enhance performance and maintain data integrity.
Ensure seamless data transition with minimal disruption to ongoing operations.
Monitor and optimize performance of data systems to ensure reliability, scalability, and cost-effectiveness within Snowflake and Databricks environments.
Collaborate with cross-functional teams, including data engineers, data scientists, analysts, and product managers, to understand data requirements and deliver solutions.
Define best practices and standards for data engineering/data warehouse processes and ensure adherence to them.
Evaluate and implement new technologies and tools to improve the efficiency and effectiveness of data pipelines.
Provide technical leadership and mentorship to junior members of the data engineering team.
Work closely with DevOps and infrastructure teams to deploy and manage data systems in production environments.
Ensure that all data solutions comply with organizational policies, industry standards, and regulatory requirements.
Collaborate with enterprise architects and IT leadership to ensure alignment of data architecture with overall IT architecture and strategies.